Major forests and plant species discrimination in Mudumalai forest region using airborne hyperspectral sensing - Bodi Surya Pratap Chandra Kishore; Amit Kumar; Purabi Saikia; Nikhil Lele; Arvind Chandra Pandey; Parul Srivastava; Bimal Kumar Bhattacharya; Mohamed Latif Khan (Journal of Asia-Pacific Biodiversity, 2020)
The present study focused on forest type classification and major plant species assemblages in Mudumalai forest region using Airborne Visible/Infrared Imaging Spectrometer Next Generation. The phytosociological analysis exhibited a total of 657 individuals (1095 individuals ha-1) of 24 tree species belonging to 22 genera and 18 families. The highest tree density was contributed by Tectona grandis (132 individuals ha-1 and 12.05% of total tree density) followed by Anogeissus latifolia (105 individuals ha-1 and 9.59% of total tree density). The support vector machine study showed the dominance of Southern Tropical Semi-Evergreen forests (31%) followed by Southern Tropical moist deciduous forests (26.7%) and Southern Tropical dry deciduous forests (24.8%) with a very high accuracy (92.37%). The comparative analysis of the existing forest types with Champion and Seth’s (1968) classification of forests exhibited a change of 30% in forest types in terms of their structure, composition, and extent over a period of 50 years. The spectral angle mapper–based study emphasized the defining role of elevation, rainfall, and temperature in species distribution, and physiognomy with dominance of A. latifolia (∼19.22%). The study implies the high spectral fidelity of airborne images for forest type mapping and plant species discrimination in tropical forests.